Analysis of ex vivo cells for disease state detection and therapeutic agent selection and monitoring

ABSTRACT

Described herein is the analysis of nanomechanical characteristics of cells. In particular, changes in certain local nanomechanical characteristics of ex vivo human cells can correlate with presence of a human disease, such as cancer, as well as a particular stage of progression of the disease. Also, for human patients that are administered with a therapeutic agent, changes in local nanomechanical characteristics of ex vivo cells collected from the patients can correlate with effectiveness of the therapeutic agent in terms of impeding or reversing progression of the disease. By exploiting this correlation, systems and related methods can be advantageously implemented for disease state detection and therapeutic agent selection and monitoring.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a divisional of U.S. patent application Ser. No.12/993,826, which is a National Stage Entry of PCT/US2008/085194, filedon Dec. 1, 2008, which claims the benefit of U.S. ProvisionalApplication Ser. No. 61/054,787, filed on May 20, 2008, and the benefitof U.S. Provisional Application Ser. No. 61/055,416, filed on May 22,2008, the disclosures of which are incorporated herein by reference intheir entireties.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with Government support under Grant NumberCA096116 and GM074509, awarded by the National Institutes of Health. TheGovernment has certain rights in the invention.

FIELD OF THE INVENTION

The invention relates generally to the analysis of nanomechanicalcharacteristics of cells. More particularly, the invention relates tosuch analysis for disease state detection and therapeutic agentselection and monitoring.

BACKGROUND

Reliable diagnosis of a human disease, such as cancer, has the potentialto alert health care providers to early onset of the disease. For manytypes of cancers, early detection can lead to early treatment, which, inturn, can significantly improve recovery and survival rates. Typically,cancer diagnosis relies on morphological examination of exfoliated oraspirated cells or surgically removed tissue samples. While consideredas the “gold standard,” diagnosis based on morphological examination canbe difficult and unreliable. In the case of metastatic adenocarcinoma,metastatic cancer cells and benign reactive mesothelial cells typicallyhave similar morphological characteristics, thereby renderingdifferentiation between the two types of cells both time-consuming andprone to errors. Indeed, certain studies have shown that morphologicalexamination alone (i.e., without any ancillary test) has an accuracy inthe range of 50 percent to 70 percent with respect to diagnosing cancerin body cavity fluids. Due to this inaccuracy, various ancillary testshave been used in conjunction with morphological examination, such ashistochemical, immunohistochemical, and ultrastructural tests. However,these ancillary tests themselves can be prone to errors with respect todiagnosing metastatic adenocarcinoma, and are typically considered asunsuitable for diagnosing other types of metastatic cancers, such assquamous cell carcinoma, melanoma, and sarcoma. Moreover, theseancillary tests often involve collection of relatively large quantitiesof samples that may not be readily available.

The past several years have seen considerable interest in identifyinglinks between nanomcchanical characteristics of cells and humandiseases, and changes in nanomcchanical characteristics of cells haverecently emerged as a potential biomarker for diagnosis of humandiseases. For example, the cytoskeleton is a subcellular structure offilaments and microtubules that provide a cell its shape, and thecytoskeleton influences both global and local nanomechanicalcharacteristics of the cell. During malignant transformation, thecytoskeleton is dynamically altered or remodeled, which, in turn, canlead to changes in nanomechanical characteristics of the cell. Despitethe progress that has been made, results of previous work remain lackingwith respect to the goal of reliably diagnosing a disease state ofliving and substantially unmodified human cells, such as those thatmight be collected in a clinical setting. In particular, previous workhas shown variability in nanomechanical characteristics among cellsobtained from cell lines. However, because cell lines have been modifiedto render them immortal, results derived from cell lines typicallycannot be readily extrapolated to predict results in an actual clinicalsetting for ex vivo human cells. In addition, previous work has shown acorrelation in whole cell nanomechanical characteristics with respect tocancer cells and benign cells. However, because the observed correlationis slight, results indicate that whole cell or global measurements maynot be sufficiently reliable for use in an actual clinical setting.

It is against this background that a need arose to develop thenanomechanical analysis and related systems and methods describedherein.

SUMMARY

One aspect of the invention relates to a nanomechanical analysis method.In one embodiment, the method includes: (1) detecting a response of abiological sample to a probing element, the biological sample includinga set of ex vivo cells; (2) based on the response, determining a set oftest values for the biological sample, the set of test values beingindicative of at least one of the Young's modulus and adhesiveness ofthe set of ex vivo cells; (3) comparing the set of test values with aset of reference values to determine a degree of correspondence betweenthe set of test values and the set of reference values, the set ofreference values being associated with at least one of a population ofcancerous cells and a population of non-cancerous cells; and (4) basedon the degree of correspondence, producing a visual indication of abiological state of the biological sample.

Another aspect of the invention relates to a computer-readable storagemedium. In one embodiment, the computer-readable storage medium includesexecutable instructions to: (1) calculate a first set of test values fora first set of ex vivo cells, the first set of test values beingindicative of at least one of the Young's modulus and adhesiveness ofthe first set of ex vivo cells, the first set of ex vivo cells beingcollected from a human patient prior to administering a therapeuticagent; (2) calculate a second set of test values for a second set of exvivo cells, the second set of test values being indicative of at leastone of the Young's modulus and adhesiveness of the second set of ex vivocells, the second set of ex vivo cells being collected from the humanpatient subsequent to administering the therapeutic agent; (3) determinea degree of correspondence between the first set of test values and thesecond set of test values; and (4) based on the degree of correspondencebetween the first set of test values and the second set of test values,produce an indication of effectiveness of the therapeutic agent for thehuman patient.

A further aspect of the invention relates to a nanomechanical analysissystem. In one embodiment, the system includes: (1) an expansionelement; (2) a cantilever having a first end and a second end, the firstend of the cantilever being connected to the expansion element; (3) aprobe disposed adjacent to the second end of the cantilever, the probebeing elongated and extending from the cantilever towards an uppersurface of a cell to be analyzed; (4) a detector element disposedadjacent to the second end of the cantilever; and (5) an opticalmicroscope disposed adjacent to a lower surface of the cell. The opticalmicroscope is configured to provide visual examination of the cell toposition the probe with respect to a central region of the cell. Theexpansion element is configured to move the first end of the cantilever,such that the probe applies a stimulus to the cell, and the detectorelement is configured to produce an output indicative of an extent ofdeflection of the second end of the cantilever in accordance with aresponse of the cell to the stimulus.

Other aspects and embodiments of the invention are also contemplated.The foregoing summary and the following detailed description are notmeant to restrict the invention to any particular embodiment but aremerely meant to describe some embodiments of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

For a better understanding of the nature and objects of some embodimentsof the invention, reference should be made to the following detaileddescription taken in conjunction with the accompanying drawings. In thedrawings, like reference numbers denote like elements, unless thecontext clearly dictates otherwise.

FIG. 1 illustrates a nanomechanical analysis system implemented inaccordance with an embodiment of the invention.

FIG. 2A and FIG. 2B illustrate operation of the system of FIG. 1,according to an embodiment of the invention.

FIG. 3 illustrates distributions of Young's modulus values for apopulation of non-cancerous ex vivo human cells and a population ofcancerous ex vivo human cells characterized according to an embodimentof the invention.

FIG. 4 illustrates distributions of adhesiveness values (in terms ofdetachment forces) for a population of non-cancerous ex vivo human cellsand a population of cancerous ex vivo human cells characterizedaccording to an embodiment of the invention.

FIG. 5 illustrates results of cell elasticity measurements performed onclinical samples, according to an embodiment of the invention.

FIG. 6 illustrates measured cell elasticity values fromcytospin-prepared clinical samples and samples prepared using an ex vivoculture procedure, according to an embodiment of the invention.

FIG. 7 illustrates results of Atomic Force Microscope analysis of cellsurface adhesion for “tumor” cells and “normal” cells from pleural fluidsamples, according to an embodiment of the invention.

FIG. 8 illustrates results of Atomic Force Microscope analysis for“tumor” cells and “normal” cells with and without exposure to Green teaextract, according to an embodiment of the invention.

DETAILED DESCRIPTION Overview

Embodiments of the invention relate generally to the analysis ofnanomechanical characteristics of cells. In particular, changes incertain local nanomechanical characteristics of ex vivo human cells cancorrelate with presence of a human disease, such as cancer, as well as aparticular stage of progression of the disease. By exploiting thiscorrelation, some embodiments of the invention can be advantageouslyused for disease state detection and therapeutic agent selection. Also,for human patients that are administered with a therapeutic agent,changes in local nanomechanical characteristics of ex vivo cellscollected from the patients can correlate with effectiveness of thetherapeutic agent in terms of impeding or reversing progression of thedisease. By exploiting this correlation, some embodiments of theinvention can be advantageously used for therapeutic agent monitoring.

Definitions

The following definitions apply to some of the aspects described withrespect to some embodiments of the invention. These definitions maylikewise be expanded upon herein.

As used herein, the singular terms “a,” “an,” and “the” include pluralreferents unless the context clearly dictates otherwise. Thus, forexample, reference to an object can include multiple objects unless thecontext clearly dictates otherwise.

As used herein, the term “set” refers to a collection of one or moreobjects. Thus, for example, a set of objects can include a single objector multiple objects. Objects of a set also can be referred to as membersof the set. Objects of a set can be the same or different. In someinstances, objects of a set can share one or more commoncharacteristics.

As used herein, the term “adjacent” refers to being near or adjoining.Adjacent objects can be spaced apart from one another or can be inactual or direct contact with one another. In some instances, adjacentobjects can be connected to one another or can be formed integrally withone another.

As used herein, the terms “inner,” “outer,” “upper,” “upwardly,”“lower,” “downwardly,” “lateral,” and “laterally” refer to a relativeorientation of a set of objects, such as in accordance with thedrawings, but do not require a particular orientation of those objectsduring manufacturing or use.

As used herein, the terms “connect,” “connected,” and “connection” referto an operational coupling or linking. Connected objects can be directlycoupled to one another or can be indirectly coupled to one another, suchas via another set of objects.

As used herein, the terms “substantially” and “substantial” refer to aconsiderable degree or extent. When used in conjunction with an event orcircumstance, the terms can refer to instances in which the event orcircumstance occurs precisely as well as instances in which the event orcircumstance occurs to a close approximation, such as accounting fortypical tolerance levels or variability of the embodiments describedherein.

As used herein with reference to a cell, the term “membrane” refers to abarrier or an interface between a cytoplasm of the cell and anextracellular environment. A cell membrane typically includes a lipidbilayer along with other biological constituents, such as polypeptides,glycoproteins, lipoproteins, and polysaccharides.

As used herein, the terms “patient” and “subject” refer to a biologicalsystem from which a biological sample can be collected or to which atherapeutic agent can be administered. A patient can refer to a humanpatient or a non-human patient. Patients can include those that arehealthy and those having a disease, such as cancer. Patients having adisease can include patients that have been diagnosed with the disease,patients that exhibit a set of symptoms associated with the disease, andpatients that are progressing towards or are at risk of developing thedisease.

As used herein, the term “biological sample” refers to a biologicalmaterial that can be collected from a patient and used in connectionwith diagnosis or monitoring of biological states. Biological samplescan include clinical samples, including body fluid samples, such as bodycavity fluids, urinary fluids, cerebrospinal fluids, blood, and otherliquid samples of biological origin; and tissue samples, such as biopsysamples, primary tumor samples, and other solid samples of biologicalorigin. Biological samples can also include those that are manipulatedin some way after their collection, such as by treatment with reagents,culturing, solubilization, enrichment for certain biologicalconstituents, cultures or cells derived therefrom, and the progenythereof.

As used herein, the term “biological state” refers to a conditionassociated with a patient or associated with a biological samplecollected from the patient. A biological state can refer to a healthystate, which corresponds to a normal condition in the substantialabsence of a disease, or a disease state, which corresponds to anabnormal or harmful condition associated with a disease. Examples ofdisease states include conditions associated with cancer, such assubstantially uncontrolled growth, invasion, and metastasis. As usedherein with reference to a biological sample collected from a patient, abiological state can refer to an ex vivo state, which corresponds to acondition in which the biological sample is substantially unmodifiedwith respect to its natural or in vivo condition within the patient. Forcertain applications, a biological sample can be considered to besubstantially unmodified with respect to its natural condition if aparticular nanomechanical characteristic of the biological samplesubstantially match a corresponding characteristic of the biologicalsample in its natural condition, such as, for example, exhibiting adifference of less than 20 percent, less than 10 percent, or less than 5percent with respect to the corresponding characteristic in its naturalcondition. Ex vivo biological samples can include those that aremanipulated in some way after their collection, so long as thebiological samples remain substantially unmodified with respect to theirnatural conditions. In the case of cells, ex vivo cells are typicallyliving and substantially unmodified cells that can be contrasted withcells obtained from cell lines, which are typically modified to renderthem immortal.

As used herein, the term “therapeutic agent” refers to a treatment thatcan be administered to a patient, whether or not effective with respectto an intended purpose or target of the treatment. Therapeutic agentscan include compounds of varying degrees of complexity that caninfluence a biological state, such as small molecules of therapeuticinterest; naturally-occurring factors such as endocrine, paracrine, orautocrine factors or factors interacting with cell receptors of anytype; intracellular factors such as those involved in intracellularsignaling pathways; and factors isolated from other natural sources.Therapeutic agents can also include agents used in gene therapy, such asDNA and RNA. Also, antibodies, viruses, bacteria, and bioactive agentsproduced by bacteria and viruses can be considered as therapeuticagents. For certain applications, a therapeutic agent can include acomposition including a set of active ingredients and a set ofexcipients.

As used herein, the terms “cancer,” “cancerous,” “malignancy,”“malignant,” and “tumor” refer to a disease in which certain cellsexhibit relatively autonomous growth, so that the cells exhibit anaberrant growth phenotype characterized by a significant loss of controlwith respect to cell proliferation.

As used herein, the term “size” refers to a characteristic dimension. Inthe case of an object that is circular or spherical, a size of theobject can refer to a diameter of the object, with the diameter beingtwice a radius of the object. In the case of an object having anon-uniform shape, a size of the object can refer to an average ofvarious orthogonal dimensions of the object. Thus, for example, a sizeof an object that is elliptical or spheroidal can refer to an average ofa major axis and a minor axis of the object. When referring to a set ofobjects as having a particular size, it is contemplated that the objectscan have a distribution of sizes around that size. Thus, as used herein,a size of a set of objects can refer to a typical size of a distributionof sizes, such as a mean size, a median size, or a peak size.

Nanomechanical Analysis System

Certain embodiments of the invention are directed to determiningnanomechanical characteristics of cells, such as ex vivo human cells,for the purpose of diagnosis, prediction, or monitoring of biologicalstates. One example of a nanomechanical characteristic is the Young'smodulus or the modulus of elasticity. The Young's modulus of a materialis a measure of elasticity or stiffness of the material, and, typically,can be expressed as a ratio of an applied stress, such as an appliedpressure, relative to a deformation or strain response within an elasticrange of the material. If sufficient pressure is applied to a surface ofa material, a displacement or movement of the surface typically occurs.If the applied pressure does not exceed an elastic limit of thematerial, the surface typically returns to its previous position oncethe applied pressure is removed. In the case of a cell, the Young'smodulus can be at least partially influenced by the cytoskeleton of thecell. During malignant transformation, the cytoskeleton can bedynamically altered or remodeled, which, in turn, can lead to changes inthe Young's modulus of the cell.

Another example of a nanomechanical characteristic is adhesiveness. Theadhesiveness of a surface of a material is a measure of a tendency ofthe surface to attach or cling to another surface and, typically, can beexpressed as an amount of force to detach or separate the surfaces onceattached to one another. In the case of a cell, an adhesiveness of thecell can be at least partially influenced by biological constituents ofa cell membrane. During malignant transformation, the nature orcomposition of the biological constituents can be dynamically altered orremodeled, which, in turn, can lead to changes in the adhesiveness ofthe cell.

According to some embodiments of the invention, a nanomcchanicalcharacteristic of a cell is determined by applying a stimulus orperturbation to the cell, detecting a response of the cell to thestimulus, and then calculating the nanomechanical characteristic of thecell based on its response. In some embodiments, a stimulus is appliedby contacting a cell membrane with a probing element, and a resultingmovement of the cell membrane is detected. Movement of the cell membranecan include lateral movement, vertical movement, stretching,contracting, or a combination thereof, and detection of the movement canbe accomplished by implementing the probing element and associatedcomponents so as to be responsive to the movement. In turn, the natureand extent of the movement can be used to calculate a nanomechanicalcharacteristic of the cell, such as its Young's modulus. In otherembodiments, a stimulus is applied by contacting a cell membrane with aprobing element, and a resulting interaction of the cell membrane withthe probing element is detected. Interaction of the cell membrane caninclude attachment to the probing element, rupturing of the cellmembrane, or a combination thereof, and detection of the interaction canbe accomplished by implementing the probing element and associatedcomponents so as to be responsive to the interaction. In turn, thenature and extent of the interaction can be used to calculate ananomechanical characteristic of the cell, such as its adhesiveness.

In some embodiments, movement or interaction of a cell membrane isdetected using an Atomic Force Microscope (“AFM”) operating in a contactmode. An AFM typically includes a spring element, such as a cantileverhaving one end adjacent to a cantilever body and another end adjacent toa probe or protrusion. The probe is elongated and extends along adirection substantially orthogonal to a lengthwise direction of thecantilever. A tip of the probe is positioned so as to be in contact witha cell, and serves as a mechanism for applying a stimulus to the cell.Movement of the cell membrane results in movement of the cantilever,such as in the form of deflection of the cantilever relative to ahorizontal plane. Since a spring constant of the cantilever can bedetermined, an amount of pressure applied to the cell membrane can bedetermined based on the extent of deflection of the cantilever as aforce is applied through the cantilever to the tip and, eventually, aspressure to the cell membrane. The force applied to the tip can beadjusted until a sufficient amount of pressure is applied to the cellmembrane, and an elastic response of the cell is then determined.Similarly, attachment of the cell membrane to the tip results inmovement of the cantilever, such as in the form of deflection of thecantilever relative to the horizontal plane. Since the spring constantof the cantilever can be determined, a detachment force to separate thetip from the cell membrane can be determined based on the extent ofdeflection of the cantilever as the tip is moved away from the cell. Itwill be appreciated that, while a spring element is sometimes referredto herein as a cantilever, the spring element can be implemented in anumber of other ways, such as a coil spring, a torsion spring, or a leafspring. Also, while a probing element is sometimes referred to herein asan AFM probe, the probing element is generally any elongated structurethat can be used to apply a stimulus to a cell. Moreover, while someembodiments are described with reference to an AFM, it will beappreciated that other types of scanning probe microscopes orforce-distance measuring devices can be used.

Desirably, an AFM tip is positioned adjacent to a central or nuclearregion of a cell and is sized so as to allow determination of aninherent nanomechanical characteristic of the cell, with little or noinfluence from a substrate supporting the cell. If the tip is positionednear an edge of the cell or is sized beyond a certain extent, the tipcan sometimes encounter resistance from the substrate beforesufficiently engaging a cell membrane, thereby yielding a result thatcan differ from an inherent nanomechanical characteristic of the cell.Also, an AFM tip is desirably sized so as to allow determination of alocal nanomechanical characteristic of a cell, rather than acorresponding whole cell or global characteristic, since the localnanomechanical characteristic can exhibit a greater correlation withrespect to presence of a human disease or with respect to a particularstage of the disease. Human cells of interest typically have sizes inthe range of about 9 micrometer (“μm”) to about 30 μm, and associatednuclear regions typically have sizes in the range of about 3 μm to about10 μm. Accordingly, for some embodiments, a radius of an AFM tip can beless than or equal to about 1 μm, such as from about 5 nanometer (“nm”)to about 900 nm, from about 5 nm to about 200 nm, from about 5 nm toabout 100 nm, from about 5 nm to about 50 nm, or from about 5 nm toabout 20 nm.

An AFM probe can be brought in contact with a cell membrane so as toapply a force in the range of about 1 pico-Newton (“pN”) to about 1micro-Newton (“μN”), such as from about 10 pN to about 100 nano-Newton(“nN”) or from about 100 pN to about 10 nN. With a contact area on thecell membrane of a radius less than or equal to about 1 μm, anassociated pressure applied to the cell membrane can be in the range ofabout 500 Pascal (“Pa”) up to about 6 kilo-Pascal (“kPa”) or more. Aresulting extent of movement of the cell membrane can be in the range ofabout 0.1 nm to about 500 nm, such as from about 1 nm to about 400 nm,from about 1 nm to about 300 nm, from about 1 nm to about 200 nm, orfrom about 1 nm to about 100 nm. Movement of the cell membrane can bedetected with a single measurement or multiple measurements, which canoccur at regular time intervals or irregular time intervals. Forexample, multiple measurements can occur at a frequency in the range ofabout 0.1 Hertz (“Hz”) to about 10 kilo-Hertz (“kHz”), such as fromabout 1 Hz to about 1 kHz, from about 1 Hz to about 100 Hz, or fromabout 1 Hz to about 10 Hz.

Attention turns to FIG. 1, which illustrates a nanomechanical analysissystem 10 implemented in accordance with an embodiment of the invention.The system 10 includes a set of components corresponding to an AFM,which is used to determine a nanomechanical characteristic of an ex vivohuman cell 14 by way of a probing element. The cell 14 is placed withina fluid medium 40, which can be any cell culture medium such asD-MEM/F-12, and is supported by a substrate 30. For reasons that arefurther described below, the substrate 30 is desirably formed of anoptically transparent or translucent material, such as glass or plastic.

As illustrated in FIG. 1, the system 10 includes a cantilever 18 havingone end 52 that is connected to a cantilever body 24, which is connectedto a cantilever support 28. The cantilever support 28, in turn, isconnected to an expansion element 26, such as a piezo-electric element,which is actuated to expand or contract so as to move the cantileversupport 28 and other connected components vertically along the z-axis.Another end 38 of the cantilever 18 is adjacent to a probe 20 includinga tip 22. The probe 20 is elongated and extends from a lower surface ofthe cantilever 18 in a direction substantially along the z-axis.

During operation of the system 10, the cantilever support 28 is moveddownwardly as a result of actuating the expansion element 26.Eventually, the tip 22 of the probe 20 is brought in contact with thecell 14, and applies a force to the cell 14. As the expansion element 26is expanded further, the force applied through the tip 22 increases andresults in deformation of the cell 14. The cantilever 18 is flexible andhas a relatively weak spring constant, and an elastic response from thecell 14 resists the applied force and results in deflection of thecantilever 18 by a certain angle α relative to a horizontal plane.

In the illustrated embodiment, the extent of deflection of thecantilever 18 is detected using a light source 32 and a photo-detectorelement 36. Referring to FIG. 1, the light source 32 is implemented as alaser, which emits a light beam 34 that is brought to focus on an uppersurface of the cantilever 18. The light beam 34 is reflected towards andstrikes the photo-detector element 36 as a laser spot. Deflection of thecantilever 18 moves the position of the laser spot with respect to thephoto-detector element 36. As illustrated in FIG. 1, the photo-detectorelement 36 is implemented as an array of photo-detectors within fourquadrants, and the photo-detectors produce outputs in response to theextent or presence of the laser spot within those quadrants. Adifference in outputs between two or more quadrants indicates theposition of the laser spot with respect to the photo-detector element 36and, thus, the extent of deflection of the cantilever 18. Othermechanisms for detecting the deflection of the cantilever 18 are alsocontemplated. For example, bending of the cantilever 18 can be detectedusing an interference-detector element, which detects the extent ofinterference between a reflected light beam and an original light beam.As another example, a piezo-resistive element or a piezo-electricelement can be included within or connected to the cantilever 18 so asto detect the extent of bending of the cantilever 18.

As illustrated in FIG. 1, the system 10 also includes a controller anddata processor 42, which is connected to various components of thesystem 10 and serves to direct operation of those components. Thecontroller and data processor 42 also processes outputs produced by thephoto-detector element 36, and performs various data retrieval andmanipulation operations for the purpose of diagnosis or monitoring ofbiological states. Referring to FIG. 1, the controller and dataprocessor 42 is connected to a display element 50, which produces visualindications for a user of the system 10. The controller and dataprocessor 42 is also connected to a memory 44, which stores computercode or executable instructions for performing various data retrievaland manipulation operations. The memory 44 also organizes dataassociated with diagnosis or monitoring of biological states, such aswithin a database.

Still referring to FIG. 1, the system 10 further includes a light source46 and an optical microscope 48, which is connected to the light source46. The light source 46 illuminates the cell 14 from above, and theoptical microscope 48 is implemented in an inverted configurationadjacent to a lower surface of the optically transparent or translucentsubstrate 30. Advantageously, the optical microscope 48 allows visualexamination of the cell 14 through the substrate 30, and allows lateralpositioning of the tip 22 over a central or nuclear region of the cell14 with a desired level of precision. The optical microscope 48 alsoallows AFM analysis to be performed in conjunction with visualexamination of the cell 14, such as for the purpose of locating andselecting the cell 14 for AFM analysis based on its morphologicalcharacteristics or its interaction with fluorescent labels.

While the single cell 14 is illustrated in FIG. 1, it is contemplatedthat multiple cells can be supported by the substrate 30 and can besubjected to similar analysis as described for the cell 14. In someinstances, multiple ex vivo human cells are prepared by subjecting abiological sample to a cytospin procedure, where a healthy or diseasestate of the cells in the biological sample is to be determined. In suchinstances, a cell-counting device, such as a Coulter Counter (BeckmanCoulter, San Diego, Calif.), can be used to ensure that a sufficientnumber of cells are obtained in accordance with the cytospin procedure.Typically, 10 to 20 living cells are desirable for AFM analysis, and thecells can be spread on the substrate 30 in a monolayer fashion. By usinga cell-counting device, a volume of a biological sample to be subjectedto the cytospin procedure can be determined in accordance with theformula:Volume=(number of cells desired)/(density of cells per unit volume)  (I)

The operation of the system 10 can be further understood with referenceto FIG. 2A and FIG. 2B. In particular, FIG. 2A illustrates the system 10in a first configuration with the probe 20 positioned at a certaindistance above the cell 14, while FIG. 2B illustrates the system 10 in asecond configuration with the probe 20 in contact with the cell 14 andpositioned over a nucleus 16 of the cell 14.

In the illustrated embodiment, the tip 22 of the probe 20 has a shapethat is substantially a circular paraboloid, and, in the secondconfiguration, the tip 22 has applied sufficient pressure to result inelastic deformation of a cell membrane 28. The Young's modulus E of thecell 14 can be calculated in accordance with the formula:E=k(d) 9/16R ^(−1/2) δ^(−3/2)   (II)where k is the spring constant of the cantilever 18, d is a deflectiondistance of the cantilever end 38, R is a radius of the tip 22, and δ isa deformation depth of the cell membrane 28. The deformation depth δ canbe calculated in accordance with the formula:δ=d _(total) −d   (III)where d_(total) is a distance that the cantilever end 52 has movedbetween the two configurations as a result of expansion of the expansionelement 26 of FIG. 1. While the illustrated embodiment has beendescribed with reference to a paraboloid tip shape, it is contemplatedthat the tip 22 can have various other shapes, and that the Young'smodulus E can be similarly calculated for those shapes. Examples ofother tip shapes include spherical shapes (e.g., associated with tipsformed by connecting spheres to cantilevers), conical shapes, shapesassociated with substantially flat or blunt tips, and shapes associatedwith tips that are curved or oblong (but not paraboloid).

Nanomechanical Characteristics of Ex Vivo Cells

Attention next turns to FIG. 3, which illustrates distributions ofYoung's modulus values for a population of non-cancerous ex vivo humancells and a population of cancerous ex vivo human cells characterizedaccording to an embodiment of the invention. Since the ex vivo cells aresubstantially unmodified with respect to their natural conditions, thedistributions illustrated in FIG. 3 are also applicable with referenceto non-cancerous in vivo human cells and cancerous in vivo human cells.

Referring to FIG. 3, certain notable differences between thedistributions can be observed. In particular, the distribution ofYoung's modulus values for non-cancerous human cells substantiallycorresponds to a log-normal distribution, while the distribution ofYoung's modulus values for cancerous human cells substantiallycorresponds to a Gaussian distribution. With respect to typical valuesof the distributions, a mean Young's modulus value and a peak Young'smodulus value for non-cancerous human cells are greater thancorresponding values for cancerous human cells, reflecting an increasedelasticity or reduced stiffness of cancerous human cells relative tonon-cancerous human cells as a result of malignant transformation. Inthe illustrated embodiment, the mean Young's modulus value fornon-cancerous human cells can be greater than or equal to about 1.5 kPa,such as from about 1.5 kPa to about 2.5 kPa, from about 1.7 kPa to about2.3 kPa, or from about 1.9 kPa to about 2.1 kPa. The mean Young'smodulus value for cancerous human cells can vary depending on a stage ofprogression or aggressiveness of the cancerous cells, reflecting anincreased elasticity or reduced stiffness of more advanced or aggressivecancerous human cells relative to less advanced or aggressive canceroushuman cells. Metastatic cancer cells typically correspond toparticularly advanced or aggressive cancerous cells, and, for the caseof metastatic cancer cells in the illustrated embodiment, the meanYoung's modulus value can be less than or equal to about 1 kPa, such asfrom about 0 kPa to about 1 kPa, from about 0.2 kPa to about 0.8 kPa, orfrom about 0.4 kPa to about 0.6 kPa. As such, the mean Young's modulusvalue of metastatic cancer cells can be smaller than the correspondingvalue for non-cancerous human cells by a factor of at least about 2,such as at least about 3 times smaller or at least about 4 timessmaller. For the case of cancerous cells of intermediate advancement oraggressiveness, the mean Young's modulus value can be in the range ofabout 0.5 kPa to about 1.5 kPa, such as from about 0.7 kPa to about 1.3kPa or from about 0.9 kPa to about 1.1 kPa. For the case of cancerouscells of lesser advancement or aggressiveness, the mean Young's modulusvalue can be in the range of about 1 kPa to about 2 kPa, such as fromabout 1.2 kPa to about 1.8 kPa or from about 1.4 kPa to about 1.6 kPa.

Still referring to FIG. 3, a spread in the distribution of Young'smodulus values for non-cancerous human cells is greater than acorresponding spread of Young's modulus values for cancerous humancells, reflecting a reduced variability in elasticity or stiffnessvalues for cancerous human cells relative to non-cancerous human cellsas a result of malignant transformation. In the illustrated embodiment,about 95 percent of Young's modulus values for non-cancerous human cellscan be in the range of about 0.9 kPa to about 4 kPa, and a standarddeviation of those values can be in the range of about 0.5 kPa to about1.5 kPa, such as from about 0.5 kPa to about 1 kPa or from about 0.6 kPato about 0.9 kPa. For the case of metastatic cancer cells in theillustrated embodiment, about 95 percent of Young's modulus values canbe in the range of about 0.2 kPa to about 0.95 kPa, and a standarddeviation of those values can be in the range of about 0.05 kPa to about0.3 kPa, such as from about 0.05 kPa to about 0.2 kPa or from about 0.05kPa to about 0.15 kPa. As such, the standard deviation of Young'smodulus values for metastatic cancer cells can be smaller than thecorresponding standard deviation for non-cancerous human cells by afactor of at least about 4, such as at least about 5 times smaller or atleast about 6 times smaller, and the distributions of Young's modulusvalues for metastatic cancer cells and non-cancerous human cells canoverlap to a limited extent, such as to an extent equal to or less thanabout 5 percent. A spread in the distribution of Young's modulus valuesfor cancerous human cells of intermediate or lesser advancement can besimilar to the corresponding spread of Young's modulus values formetastatic cancer cells.

FIG. 4 illustrates distributions of adhesiveness values (in terms ofdetachment forces) for a population of non-cancerous ex vivo human cellsand a population of cancerous ex vivo human cells characterizedaccording to an embodiment of the invention. Since the ex vivo cells aresubstantially unmodified with respect to their natural conditions, thedistributions illustrated in FIG. 4 are also applicable with referenceto non-cancerous in vivo human cells and cancerous in vivo human cells.

Referring to FIG. 4, the distribution of adhesiveness values fornon-cancerous human cells substantially corresponds to a Gaussiandistribution, and the distribution of adhesiveness values for canceroushuman cells also substantially corresponds to a Gaussian distribution.However, with respect to typical values of the distributions, a meanadhesiveness value for non-cancerous human cells is greater than acorresponding value for cancerous human cells, reflecting a reducedadhesiveness of cancerous human cells relative to non-cancerous humancells as a result of malignant transformation. In the illustratedembodiment, the mean adhesiveness value for non-cancerous human cellscan be greater than or equal to about 40 pN, such as from about 40 pN toabout 60 pN, from about 45 pN to about 55 pN, or from about 48 pN toabout 52 pN. The mean adhesiveness value for cancerous human cells canvary depending on a stage of progression or aggressiveness of thecancerous cells, reflecting a reduced adhesiveness of more advanced oraggressive cancerous human cells relative to less advanced or aggressivecancerous human cells. For the case of metastatic cancer cells in theillustrated embodiment, the mean adhesiveness value can be less thanabout 40 pN, such as from about 25 pN to about 39 pN, from about 30 pNto about 39 pN, or from about 33 pN to about 37 pN. As such, the meanYoung's modulus value of metastatic cancer cells can be smaller than thecorresponding value for non-cancerous human cells by a factor of atleast about 1.2, such as at least about 1.3 times smaller or at leastabout 1.4 times smaller. For the case of cancerous cells of intermediateadvancement or aggressiveness, the mean adhesiveness value can be in therange of about 30 pN to about 50 pN, such as from about 35 pN to about45 pN or from about 38 pN to about 42 pN. For the case of cancerouscells of lesser advancement or aggressiveness, the mean adhesivenessvalue can be in the range of about 35 pN to about 55 pN, such as fromabout 40 pN to about 50 pN or from about 43 pN to about 47 pN.

Still referring to FIG. 4, a spread in the distribution of adhesivenessvalues for non-cancerous human cells is greater than a correspondingspread of adhesiveness values for cancerous human cells, reflecting areduced variability in adhesiveness values for cancerous human cellsrelative to non-cancerous human cells as a result of malignanttransformation. In the illustrated embodiment, about 95 percent ofadhesiveness values for non-cancerous human cells can be in the range ofabout 25 pN to about 60 pN, and a standard deviation of those values canbe in the range of about 8 pN to about 20 pN, such as from about 10 pNto about 18 pN or from about 13 pN to about 18 pN. For the case ofmetastatic cancer cells in the illustrated embodiment, about 95 percentof adhesiveness values can be in the range of about 20 pN to about 45pN, and a standard deviation of those values can be in the range ofabout 2 pN to about 10 pN, such as from about 2 pN to about 8 pN or fromabout 4 pN to about 6 pN. As such, the standard deviation ofadhesiveness values for metastatic cancer cells can be smaller than thecorresponding standard deviation for non-cancerous human cells by afactor of at least about 1.5, such as at least about 2 times smaller orat least about 3 times smaller. A spread in the distribution ofadhesiveness values for cancerous human cells of intermediate or lesseradvancement can be similar to the corresponding spread of adhesivenessvalues for metastatic cancer cells.

Diagnosis, Prediction, and Monitoring of Biological States Based onNanomechanical Characteristics of Ex Vivo Cells

Referring to FIG. 3 and FIG. 4, the distributions of Young's modulusvalues and adhesiveness values for non-cancerous human cells andcancerous human cells can form the basis of nanomechanical assays forcancer. In particular, the distributions illustrated in FIG. 3 and FIG.4 can serve as reference values to which test values determined for exvivo human cells in clinical samples can be compared for diagnosis,prediction, and monitoring of cancer in human patients.

Advantageously, nanomechanical assays can be performed on a variety ofclinical samples for diagnosis, prediction, and monitoring of differenttypes of cancer. For example, nanomechanical assays can be performed onbody cavity fluids for diagnosis, prediction, and monitoring ofmetastatic adenocarcinoma. As another example, nanomechanical assays canbe performed on urinary fluids for diagnosis, prediction, and monitoringof bladder cancer. As a further example, nanomechanical assays can beperformed on primary tumor samples for diagnosis, prediction, andmonitoring of breast cancer. Nanomechanical assays can be performed inconjunction with visual examination of ex vivo human cells, such as inaccordance with morphological examination or immunofluorescence labelingof the cells. Such visual examination can facilitate locating andselecting a subset of cells for nanomechanical assays based onmorphological characteristics or interaction of the subset of cells withfluorescent labels.

According to an embodiment of the invention, a nanomechanical assay canbe implemented for diagnosis of cancer and, in particular, as adiagnostic screen or test for the presence of cancer in a human patient.The nanomechanical assay can also be implemented as a prognostic screenor test for predicting the likelihood of developing cancer. Inparticular, a clinical sample can be collected from the human patient,and AFM analysis can be performed to determine test values of a set ofnanomechanical characteristics of an ex vivo human cell in the clinicalsample. The set of nanomechanical characteristics can include either of,or both, the Young's modulus and adhesiveness of the cell. For example,measurements can be performed using the system 10 of FIG. 1 to determinea set of Young's modulus values for the cell or a set of adhesivenessvalues for the cell. Multiple test values of each nanomechanicalcharacteristic can be determined for the cell, and these multiple testvalues can be subjected to statistical analysis to determine aneffective or typical test value for the cell. Also, multiple ex vivohuman cells in the clinical sample can be subjected to AFM analysis todetermine respective test values of the set of nanomechanicalcharacteristics. For example, measurements can be performed using thesystem 10 of FIG. 1 to determine a set of Young's modulus values foreach cell of a selected subset of cells or a set of adhesiveness valuesfor each cell of the selected subset of cells. Multiple test valuesacross different cells in the clinical sample can be subjected tostatistical analysis to determine an effective or typical test value forthe cells.

Next, test values of the set of nanomechanical characteristics resultingfrom AFM analysis can be compared with reference values of the set ofnanomechanical characteristics. In particular, a comparison can beperformed with respect to either of, or both, reference values fornon-cancerous cells and reference values for cancerous cells, andresults of the comparison can be indicative of whether the test valuesresulting from AFM analysis are substantially consistent with orsubstantially correspond to reference values for non-cancerous cells orcancerous cells. It will be appreciated that a determination ofconsistency or correspondence with one type of cell can reflectinconsistency or lack of correspondence with another type of cell, andvice versa. In such manner, the absence or presence of cancer in thehuman patient can be reliably diagnosed, or the likelihood of developingcancer can be reliably predicted. Advantageously, reliable diagnosis orprediction of cancer has the potential to alert a health care providerto early onset of cancer in the human patient, which can lead to earlytreatment and significantly improved recovery and survival rates.

For example, using the system 10 of FIG. 1, a set of Young's modulusvalues for an ex vivo human cell can be compared with reference valuesas illustrated in FIG. 3. If the set of Young's modulus values fallwithin a typical range of reference values for cancerous cells (e.g.,accounting for 95 percent of the reference values) and outside a typicalrange of reference values for non-cancerous cells, a determination canbe made that the cell is likely cancerous or is likely progressingtowards developing cancer. Conversely, if the set of Young's modulusvalues fall within the typical range of reference values fornon-cancerous cells and outside the typical range of reference valuesfor cancerous cells, a determination can be made that the cell is likelynon-cancerous or benign. If the set of Young's modulus values fallwithin an overlapping range for non-cancerous cells and cancerous cells,an inconclusive determination can be made, and analysis of additionalcells in the clinical sample can be performed. As an alternative to, orin conjunction with, the manner of comparison described above, the setof Young's modulus values can be compared with typical reference valuesas illustrated in FIG. 3. In particular, a determination can be madewhether the cell is likely cancerous or non-cancerous based on proximityof the set of Young's modulus values to a typical reference value forcancerous cells (e.g., a mean reference value) or proximity of the setof Young's modulus values to a typical reference value for non-cancerouscells. A similar manner of comparison can be performed using aneffective or typical test value for a single cell or an effective ortypical test value across different cells in the clinical sample.Moreover, a similar manner of comparison can be performed usingadhesiveness values resulting from AFM analysis and reference values asillustrated in FIG. 4.

For certain applications, multiple test values across different cells inthe clinical sample can be subjected to statistical analysis todetermine the nature or extent of a distribution of those test values,and results of the statistical analysis can be compared with referencedistributions as illustrated in FIG. 3 and FIG. 4. For example, ifYoung's modulus values of the cells can be substantially fitted to aGaussian distribution (e.g., a reference Gaussian distribution asillustrated in FIG. 3), a determination can be made that the cells arelikely cancerous or are likely progressing towards developing cancer.Conversely, if the Young's modulus values can be substantially fitted toa log-normal distribution (e.g., a reference log-normal distribution asillustrated in FIG. 3), a determination can be made that the cells arelikely non-cancerous or benign. If the Young's modulus values exhibitcharacteristics consistent with both a Gaussian distribution and alog-normal distribution, either an inconclusive determination can bemade or a determination can be made that both types of cells are presentin the clinical sample. As an alternative to, or in conjunction with,the manner of comparison described above, a spread in the Young'smodulus values can be compared with spreads in reference values asillustrated in FIG. 3. In particular, a determination can be madewhether the cells are likely cancerous or non-cancerous based onproximity of the spread in the Young's modulus values to a spread inreference values for cancerous cells (e.g., a standard deviation) orproximity of the spread in the Young's modulus values to a spread inreference values for non-cancerous cells. A similar manner of comparisoncan be performed using adhesiveness values resulting from AFM analysisand reference distributions as illustrated in FIG. 4.

In addition to detecting or predicting cancer, an embodiment of ananomechanical assay can be implemented for diagnosis or prediction of aparticular stage of progression of cancer in a human patient. Inparticular, a clinical sample can be collected from the human patient,and AFM analysis can be performed to determine test values of a set ofnanomcchanical characteristics in a similar manner as described above.Next, the test values of the set of nanomechanical characteristicsresulting from AFM analysis can be compared with reference values of theset of nanomechanical characteristics. For certain applications, thedetection of cancer in the clinical sample by itself can be indicativeof a particular stage of cancer in the human patient. For example, bodycavities are typically the site of metastasis, and the detection ofcancer in body cavity fluids can be indicative of widespread cancer. Forother applications, a comparison can be performed with respect tocancerous cells of different degrees of advancement or aggressiveness,and results of the comparison can be indicative of whether the testvalues resulting from AFM analysis are substantially consistent with orsubstantially correspond to reference values for cancerous cells of aparticular degree of advancement. It will be appreciated that adetermination of consistency or correspondence with cancerous cells ofone degree of advancement can reflect inconsistency or lack ofcorrespondence with cancerous cells of another degree of advancement,and vice versa. In such manner, a particular stage of cancer in thehuman patient can be reliably diagnosed, or the likelihood of furtherprogression of cancer towards that stage can be reliably predicted.

For example, using the system 10 of FIG. 1, a set of Young's modulusvalues for an ex vivo human cell can be compared with reference valuesas illustrated in FIG. 3. If the set of Young's modulus values fallwithin a typical range of reference values for metastatic cancer cellsand outside a typical range of reference values for non-cancerous cellsor cancerous cells of intermediate or lesser advancement, adetermination can be made that the cell is likely metastatic or islikely progressing towards metastasis. If the set of Young's modulusvalues fall within the typical range of reference values for cancerouscells of intermediate or lesser advancement and outside the typicalrange of reference values for non-cancerous cells or metastatic cancercells, a determination can be made that the cell likely has or isdeveloping cancer of intermediate or lesser advancement. If the set ofYoung's modulus values fall within an overlapping range of referencevalues, an inconclusive determination can be made, and analysis ofadditional cells in the clinical sample can be performed. As analternative to, or in conjunction with, the manner of comparisondescribed above, the set of Young's modulus values can be compared withtypical reference values as illustrated in FIG. 3. In particular, adetermination can be made of the degree of advancement of cancer in thecell based on proximity of the set of Young's modulus values to atypical reference value for metastatic cancer cells (e.g., a meanreference value) or proximity of the set of Young's modulus values to atypical reference value for non-cancerous cells or cancerous cells ofintermediate or lesser advancement. A similar manner of comparison canbe performed using an effective or typical test value for a single cellor an effective or typical test value across different cells in theclinical sample. Also, multiple test values across different cells inthe clinical sample can be subjected to statistical analysis todetermine the nature or extent of a distribution of those test values,and results of the statistical analysis can be compared with referencedistributions for cancerous cells of different degrees of advancement oraggressiveness. Moreover, a similar manner of comparison can beperformed using adhesiveness values resulting from AFM analysis andreference values as illustrated in FIG. 4.

By providing reliable diagnosis or prediction of a particular type ofcancer in a human patient, an embodiment of a nanomechanical assay canbe implemented for selection of a therapeutic agent suitable for thattype of cancer. Also, by providing reliable diagnosis or prediction of aparticular stage of cancer in the human patient, the nanomechanicalassay can be implemented for selection of a therapeutic agent suitablefor that stage of cancer. Examples of therapeutic agents that can beused to treat cancer include Green tea extract (“GTE”) and variouschemotherapy drugs such as cisplatin (orcis-diamminedichloridoplatinum(II)) and paclitaxel. It will beappreciated that certain therapeutic agents can be suitable for aparticular type of cancer of one degree of advancement oraggressiveness, while other therapeutic agents can be suitable for thesame or a different type of cancer of another degree of advancement.Suitability of a therapeutic agent can involve considerations related toits effectiveness in terms of impeding or reversing progression ofcancer as well as considerations related to its potential side effects.For example, if test values resulting from AFM analysis are indicativeof metastasis or progression towards metastasis, a therapeutic agentsuitable for particularly advanced or aggressive cancer can be selectedfor the human patient. Conversely, if the test values resulting from AFManalysis are indicative of cancer of intermediate or lesser advancement,another therapeutic agent can be selected for the human patient. In suchmanner, treatment of the human patient can be tailored in accordancewith a particular type and a particular stage of cancer in the humanpatient, which can significantly improve recovery and survival rates.

Once a therapeutic agent is selected for a human patient, an embodimentof a nanomechanical assay can be implemented for monitoringeffectiveness of the therapeutic agent in terms of impeding or reversingprogression of cancer in the human patient. In particular, theeffectiveness of the therapeutic agent can be determined byadministering the therapeutic agent to the human patient, collecting aclinical sample from the human patient subsequent to administering thetherapeutic agent, and performing AFM analysis on the clinical sample ina similar manner as described above. The therapeutic agent can beadministered in a variety of ways, such as orally, via inhalation,intravenously, or a combination thereof. Typically, an effective dose ofthe therapeutic agent is administered to the human patient, and theeffective dose can be determined using a variety of pharmacologicaltechniques.

Next, post-treatment test values of a set of nanomechanicalcharacteristics can be compared with reference values of the set ofnanomechanical characteristics. For certain applications, a comparisoncan be performed with respect to reference values as illustrated in FIG.3 and FIG. 4, and results of the comparison can be indicative of whetherthe post-treatment test values are substantially consistent with orsubstantially correspond to reference values for non-cancerous cells orcancerous cells of a lesser degree of advancement. For otherapplications, baseline or pre-treatment test values of the set ofnanomechanical characteristics can be determined by collecting aclinical sample from the human patient prior to administering thetherapeutic agent, and performing AFM analysis on the clinical sample ina similar manner as described above. The pre-treatment test values canserve as reference values to which the post-treatment test values arecompared. Results of the comparison can be indicative of whether thepost-treatment test values are shifted towards the absence of cancer ortowards cancer of a lesser degree of advancement.

EXAMPLES

The following examples describe specific aspects of some embodiments ofthe invention to illustrate and provide a description for those ofordinary skill in the art. The examples should not be construed aslimiting the invention, as the examples merely provide specificmethodology useful in understanding and practicing some embodiments ofthe invention.

Example 1 Methodology for Sample Preparation, AFM Measurements,Immunofluorescence Labeling, and Statistical Analysis

Cytological Sample Preparation (ex vivo culture): Body cavity fluidsamples were collected and processed using a set of standard protocolsfor cytological analysis, including Papanicolaou stain, Gimsa stain, andcellblock preparation. An aliquot of each sample (10 ml) was centrifugedat about 500 g for about 10 min. Cell pellets were re-suspended withMEM-F 12 culture medium and incubated for about 12 hr at about 37° C. in5 percent CO₂ and 95 percent air. The culture medium was changed justprior to AFM measurements to wash off any dead and untouched cells.

AFM Measurements: Studies were conducted using a modified systemincluding a Nanoscope IV Bioscope (Veeco Digital Instruments) combinedwith an inverted optical microscope (Nikon eclipse TE200). Thiscombination permitted lateral positioning of an AFM tip over a centralor nuclear region of a cell with micrometer precision. A scan size forall measurements was set to about 0 nm to maintain a substantiallyconstant position over the cell, and, using an AFM software, the tip wasbrought into contact with the central region of the cell. AFMmeasurements were collected at about 37° C. using sharpened siliconnitride cantilevers with experimentally determined spring constants ofabout 0.02 N m⁻¹ and a tip radius of less than about 20 nm.Force-displacement curves were recorded at about 1 Hz for determinationof Young's modulus, E. E was determined by converting theforce-displacement curves into force-indentation curves and fitting withthe Hertz model, which represents the indentation of an elastic objectusing a stiff conical indenter. A half opening angle of the AFM tip wasabout 36°, and a Poisson ratio of the cell was taken to be 0.5, as istypical for soft biological materials. To reduce damage to the cellsurface and to reduce any substrate-induced effects, measurements wereperformed in force ranges resulting in shallow indentations of the cell(<400 nm or <500 nm).

Immunofluorescence Triple Labeling: Two types of triple labeling assayswere performed, namely DNA/F-actin/Ber-EP4 and DNA/Calretinin/Ber-EP4.For both assays, cells were fixed first with 3.7 percent formaldehydefor about 30 min at room temperature, washed with 1× PBS three times,and then incubated with 1 percent BSA in PBS pH 7.4 for about 30 min.For DNA/F-actin/Ber-EP4 labeling, cells were first incubated with mouseanti-human Ber-EP4 (DAKO) at about 1:300 dilution for about 1 hr,followed by Cy3-conjugated AffiniPure goat anti-mouse IgG(H+L) (JacksonImmunoResearch Lab) at about 1:200 dilution for about 30 min, and thenwith BODIPY FL phallacidin F-actin (Molecular Probes) at about 1:40dilution for about 30 min. Subsequently, cells were incubated with about1:10,000 DAPI for about 5 min. For DNA/Calretinin/Ber-EP4 labeling,cells were first incubated with mouse anti-human Ber-EP4 (DAKO) at about1:300 dilution for about 1 hr, followed by Cy3-conjugated AffiniPuregoat anti-mouse IgG(H+L) (Jackson ImmunoResearch Lab) at about 1:200dilution for about 30 min. Cells were then further incubated with about1:600 diluted rabbit anti-human Calretinin antibody (Zymed) for about 1hr, with FITC-conjugated AffiniPure goat anti-rabbit IgG(H+L) (JacksonImmunoResearch Lab) at about 1:50 dilution for about 30 min, and thenfollowed by about 1:10,000 DAPI for about 5 min. All incubations wereperformed at room temperature, with three PBS washing steps in between.Cells were covered with a mounting medium for fluorescence microscopicexamination (Zeiss). Images were taken using an Olympus BX-40 microscopewith a 40× objective.

Statistical Analysis: Data were expressed as mean values±standarddeviation, and statistical significance of differences in mean valueswas assessed using a two-sample independent Student's t-test at the 95percent confidence level. Differences in mean values were expressedusing exact P values.

Example 2 Elasticity of Metastatic Cancer Cells and Benign ReactiveMesothelial Cells (Ex Vivo Culture)

Using the methodology of Example 1, elasticity of pathologically definedhuman metastatic cancer cells and benign reactive mesothelial cells inhuman body cavity (pleural) fluid clinical samples was determined usingan AFM. Analysis of body cavity fluid samples, rather than primary tumorsamples, was selected because tumor cells in body fluids are typicallyall metastatic in nature and thus provide a clonal population ofmetastatic cells for analysis. Additionally, the co-existence of bothbenign cells and metastatic cancer cells in a single sample provides anative internal control.

Body cavities, including pleural, pericardial, and peritoneal cavities,are typically covered by serous membranes including a single row of flatmesothelial cells on the surface and an underlying sub-mesotheliallayer, which covers a relatively large surface area in close contactwith major organs of the body. Because of their continuity with thelymphatic system, body cavities are typically the site of metastasis,and metastatic malignant effusions can be indicative of widespreadcancer. Current cancer cell detection typically relies on qualitativemorphological examination of changes in cell shape resulting frombiochemical alterations, such as cytoskeletal remodeling. However,morphological examination of cells collected from an effusion can bedifficult to diagnose because of the reactivity of mesothelial cells inmimicking metastatic cancer cells morphologically, including featuringenlarged nuclei and increased nuclear and cytoplasmic ratios, amongother cytomorphological features.

In connection with AFM measurements, samples were collected frompatients with suspected metastatic adenocarcinoma. The samples werecentrifuged, and cell pellets were re-suspended in a culture medium forabout 12 hr, which was based on time-culture experiments to establish anoptimum incubation time for cell-substrate adherence for nanomechanicalanalysis while reducing artifacts resulting from in vitro culture. The12 hr incubation time also allowed differentiation of benign andmalignant cells based on their ex vivo growth and morphologicalcharacteristics. That is, cancer cells typically displayedanchorage-independent growth patterns, such as rounding of cells, whilebenign mesothelial cells typically displayed a relatively large, flatmorphology. In such manner, AFM analysis was readily performedseparately on the two cell populations. For each sample, eight probablebenign mesothelial cells (“normal”) and eight probable malignant cells(“tumor”) were selected from a culture dish for ex vivo AFM analysis.This selection of probable malignant cells was performed except innegative cases where only benign cells were present. The AFM analysiswas performed in an alternate fashion to ensure similar conditions wereapplied for both cell populations, without prior knowledge of results ofcytomorphological analysis. For each clinical sample, a new cantileverwas used to avoid contribution of potential artifacts. Cytomorphologicaland immunohistochemical confirmatory analysis, AFM analysis, andimmunofluorescence analyses were performed independently. Thecytomorphological analysis was performed on its own population of cells,but the immunofluorescence and AFM analyses were performed on the samepopulation of cells. However, all of the cell populations were obtainedfrom the same pleural effusion sample. AFM measurements were performedat about 37° C. at a rate of about 1 Hz. Force-displacement curves wererecorded on each cell to determine a relative elasticity or stiffness(Young's modulus, E) of the individual cell, yielding values of E foreach cell type per sample. Table 1 below sets forth results of theanalyses.

TABLE 1 Elasticity Elasticity Sample Cytological (kPa) “Tumor” (kPa) No.Age/Sex Clinical History Analysis cells “Normal” cells 1 52/FemaleNon-small cell carcinoma of Positive for 0.56 ± 0.09 2.10 ± 0.79 thelung metastatic malignant cells 2 60/Female Non-small cell carcinoma ofPositive for 0.52 ± 0.12 2.05 ± 0.87 the lung metastatic malignant cells3 49/Female Breast ductal Positive for 0.50 ± 0.08 1.93 ± 0.50adenocarcinoma metastatic malignant cells 4 85/Male Pancreaticadenocarcinoma Positive for 0.54 ± 0.08 0.54 ± 0.12 metastatic malignantcells 5 40/Male Liver cirrhosis Negative for N/A 1.86 ± 0.50 malignantcells 6 47/Male Fever and hepatic failure Negative for N/A 1.75 ± 0.61malignant cells 7 92/Female Anasarca peripheral oedema Negative for N/A2.09 ± 0.98 malignant cells

To confirm that selected cell populations actually correspond tomalignant and benign mesothelial cells, immunofluorescence triplelabeling assays of the samples were performed. Labeling forDNA/Ber-EP4/F-actin and DNA/Ber-EP4/Calretinin both showed staining ofsmall, round cells for Ber-EP4 (red), which is a biomarker formetastatic adenocarcinoma cells, thus confirming that the round orballed cells were indeed metastatic adenocarcinoma cells. Moreover,larger, flat cells were positive for Calretinin staining, which isindicative of normal mesothelial cells, thus confirming their opticalmorphology. Immunofluorescence analysis showed that the small, roundcells were not apoptotic, dead, or mitotic, and had intact DNA.

Results of cell elasticity measurements (Young's modulus, E) performedon the clinical samples are illustrated in FIG. 5. Data collected fromthe seven clinical samples (positive for metastatic malignant cells,n=40; negative for malignant cells, n=48) yielded average E values (meanvalue±standard deviation) of about 0.53±0.10 kPa for all malignant cellsand about 1.97±0.70 kPa for all benign mesothelial cells (see FIG. 5Athrough FIG. 5C). A two-sample independent 1-test conducted for themalignant and benign cell populations showed that the population averagevalues were significantly different from each other at the 95 percentconfidence level (P=8.72×10⁻²²). In addition, malignant cell elasticitymeasurements from a single clinical sample yielded an average cellelasticity (mean value±standard deviation) of about 0.56±0.09 kPa (secFIG. 5D and FIG. 5E) (Table 1, Sample No. 1). However, for this clinicalsample, morphologically determined benign mesothelial cells exhibited asignificantly increased average cell elasticity (mean value±standarddeviation) of about 2.10±0.79 kPa (see FIG. 5D and FIG. 5F;P=7.77×10⁻⁵). Also of note, the malignant and benign mesothelial cellsexhibited different trends, with elasticity measurements for themalignant cells and the benign mesothelial cells represented by Gaussian(normal) and log-normal fits, respectively. The malignant cellsdisplayed a narrow, spiked peak with relatively little spread, while thebenign mesothelial cells displayed a broad peak. Similarly, elasticitymeasurements collected on a single negative clinical sample yielded anaverage cell elasticity (mean value±standard deviation) of about2.09±0.98 kPa (see FIG. 5G; n=8) (Table 1, Sample No. 7). The dataindicate that metastatic cancer cells are about 73±11 percent less stiffthan benign mesothelial cells in the same clinical sample, and whencompared to clinical samples collected from other patients. The observedsimilarity in the data from patient to patient and from cell to cell isindicative of a parallel across patient effusions and across cell types.

FIG. 5H and FIG. 5I illustrate Gaussian fits of elasticity datacollected on an individual clinical sample (Table 1, Sample No. 4).Following ex vivo culture, there appeared to be two populations ofcells: one cell population that was larger and more flat (suggestive ofbenign mesothelial cells); and the other cell population that was morerounded and balled (suggestive of malignant cells). Despite thedifference in morphology in ex vivo culture, nanomechanical analysisconcluded that the cells were all malignant cells. Average elasticityvalues (mean value±standard deviation) for the morphologicallyclassified malignant cells and morphologically classified benign cellswere 0.54±0.08 kPa and 0.54±0.12 kPa, respectively (see 5H and FIG. 5I;n=8). These population elasticity values were not statisticallydifferent, and indicated the presence of a single population ofmalignant cells. Subsequent immunohistochemical staining with a set ofmarkers, including Calretinin, B72.3, and Ber-EP4, confirmed that thesample included one cell population, which was malignant based onimmunohistochemical findings (negative for Calretinin and positive forBer-EP4 and B72.3). Additionally, this particular case demonstrated thelack of correlation between ex vivo cultured cell morphology andmeasured elasticity, and that it is unlikely that the ex vivo culturedmorphological differences influenced the measured elasticity.

By way of summary, the results indicate that a biologically driven shifttowards a decrease in cell elasticity correlates with an increase inmetastatic potential. Under similar conditions, elasticity of metastaticcancer cells is more than about 70 percent lower than that of normalreactive mesothelial cells in the same clinical sample, and whencompared to other pleural effusions or other patients with differentclinical histories (Table 1). Despite morphological overlap betweenmalignant and benign cell types, which can impede cytomorphological andimmunohistochemical diagnosis of malignant cells, nanomechanicalanalysis provided the ability to differentiate malignant cells, therebyallowing the detection of metastatic cancer cells in body fluids. Also,the distribution of measured cell elasticity for cancer cells wasobserved to fit a normal distribution and to be over five times narrowerthan the corresponding distribution for benign mesothelial cells, whichwas observed to fit a log-normal distribution.

Example 3 Elasticity of Metastatic Cancer Cells and Benign ReactiveMesothelial Cells (Cytospin Procedure Without Ex Vivo Culture)

To further confirm that measured differences in elasticity betweencancer and benign cells were not an artifact of ex vitro culture,measurements were performed using a cytospin procedure without ex vivoculture, which yielded cell populations that were substantiallyindistinguishable in terms of morphology. By way of preview, theresulting elasticity values for cancer cells and benign mesothelialcells were similar to those obtained using a 12 hr ex vivo cultureprocedure. The results demonstrate that nanomechanical analysis isindicative of cell type, even when using different preparationprocedures and different substrates.

The cytospin procedure was a modified version of that described inMotherby, H. et al., Pleural Carcinosis Confirmed by AdjuvantCytological Methods: A Case Report, Diag. Cytopathology 19, 370-374(1998), the disclosure of which is incorporated herein by reference inits entirety. In accordance with the cytospin procedure, cells weregently centrifuged on a slide (2 min at 500 g). The slide was thencovered with a culture medium (90 percent D-MEM/F-12 (Ham) medium). AFManalysis was performed within about 2 hr of sample preparation topreserve cell viability. The speed and time of centrifugation weredetermined to allow initial cell-substrate adhesion with reducedalteration of nanomechanical characteristics of the cells. Without exvivo culture, different cell types displayed substantially similarmorphological characteristics. In particular, all cells, whether “tumor”or “normal,” appeared rounded and were substantially indistinguishableby morphology alone. The following sets forth data from three clinicalsamples (2 positive samples):

“Tumor” (n=38 measurements):

-   -   Young's modulus, E=0.50±0.26 kPa (mean value±standard deviation)

“Normal” (n=27 measurements):

-   -   Young's modulus, E=2.73±1.30 kPa (mean value±standard deviation)

These average elasticity values are similar to those obtained using the12 hr ex vivo culture procedure. The results indicate thatnanomechanical analysis can be used to distinguish malignant cells frombenign cells even when the cells have similar morphology.

Example 4 Elasticity of Metastatic Cancer Cells and Benign ReactiveMesothelial Cells (Ex Vivo Culture and Cytospin Procedure Without ExVivo Culture)

AFM analysis was performed using both the ex vivo culture procedure ofExample 1 and a cytospin procedure without ex vivo culture. Inaccordance with the cytospin procedure, cells were gently centrifuged ona slide (1 min at 500 g), and the slide was then covered with a culturemedium (90 percent D-MEM/F-12 (Ham) medium). AFM analysis was performedwithin about 1-2 hr of sample preparation to preserve cell viability.The speed and time of centrifugation were determined to allow initialcell-substrate adhesion with reduced alteration of nanomechanicalcharacteristics of the cells. Without ex vivo culture, different celltypes displayed substantially similar morphological characteristics. Inparticular, all cells, whether “tumor” or “normal,” appeared rounded andwere substantially indistinguishable by morphology alone. However,cancer cells typically display nuclear characteristics that differslightly from that of benign cells, and this distinction provided amechanism to select cell types.

FIG. 6 illustrates measured cell elasticity values fromcytospin-prepared clinical samples that were collected from patientswith suspected metastatic adenocarcinoma. Analysis of allcytospin-prepared samples (metastatic cancer cells, n=64; benignreactive mesothelial cells, n=69) yielded average elasticity values(mean value±standard deviation) for all cancer and benign cells of about0.38±0.20 kPa and 2.53±1.30 kPa, respectively (see FIG. 6A and FIG. 6B).A two sample independent t-test conducted for cancer and benign cellpopulations showed that the population values were significantlydifferent from each another at the 95 percent confidence level(P=1.67×10⁻²⁵). Immunofluorescence triple labeling assays of the sampleswere performed using a combination of markers, including Calretinin(positive in benign mesothelial cells but negative for metastaticadenocarcinoma), BerEP4, and B72.3 (positive for metastaticadenocarcinoma but negative for benign mesothelial cells), to confirmthat the selected cell populations corresponded to cancer cells andbenign mesothelial cells. Immunofluorescence analysis also showed intactDNA, indicating that the cells were not dead, mitotic, or apoptotic.

FIG. 6 also illustrates measured cell elasticity values for cancer cellsand benign mesothelial cells prepared using the ex vivo cultureprocedure (see FIG. 6C and FIG. 6D). The average cell elasticity values(mean value±standard deviation) obtained using the ex vivo cultureprocedure were 0.53±0.10 kPa and 1.97±0.70 kPa for cancer cells andbenign cells, respectively (metastatic cancer cells, n=40; benignreactive mesothelial cells, n=48; P=8.72×10²²). The results indicate asubstantial similarity in the measured elasticity values of differentcell types, regardless of culture procedure. Also, the results indicatethat elasticity of cancer cells is about 70 percent to about 80 percentless than that of benign cells, even when measured using a 1 mincytospin procedure that yields morphologically indistinguishable celltypes. Advantageously, the cytospin procedure served to avoid lengthyculture times and to produce cells substantially similar to those underin vivo conditions, thus reducing any artifacts due to ex vivo cultureconditions. Furthermore, nanomechanical analysis of cancer cellsprepared using both the cytospin and the ex vivo culture proceduresyielded a narrow distribution compared to benign mesothelial cells.Benign cells displayed a significantly larger spread in distribution ofthe measured cell elasticity values for both the cytospin and the exvivo culture procedures. The results indicate that nanomechanicaldifferences between cancer and benign cells, rather than differentmorphology resulting from ex vivo culture conditions, are the primarysource of differences in measured cell elasticity between the celltypes.

Example 5 Adhesiveness of Metastatic Cancer Cells and Benign ReactiveMesothelial Cells

Pleural effusion clinical samples were collected from patients withmetastatic adenocarcinoma, and were prepared using a set of standardprotocols as previously described in Example 1. The samples were placedin culture for about 12 hr. For each sample, probable benign cells(“normal”) and probable malignant cells (“tumor”) were selected fromtheir culture for analysis using an AFM. The cells were selected basedon their growth pattern in culture, as previously described. AFManalysis was conducted in an alternate fashion to ensure similarconditions for both the “tumor” cells and the “normal” cells, andwithout knowledge of results from cytomorphological analysis.Subsequently, the AFM analysis was confirmed by immunohistochemicalstaining for biomarkers using cellblock.

Real-time, in vivo AFM measurements were performed on the clinicalsamples to determine cellular adhesive force as a function ofnanomechanical characteristics of surface adhesive molecules. Afterpositioning an AFM tip over a central region of a cell, the tip wasbrought into contact and pressed against a surface of the cell. Duringtip retraction from the cell surface, rupture events typically occurred,which indicate tip-cell surface adhesive interactions specific for eachcell type. The results of the AFM analysis of the cell surface adhesionfor “tumor” cells and “normal” cells from the pleural fluid samples areset forth in FIG. 7 and Table 2 below.

TABLE 2 Sample Adhesion (pN) Adhesion (pN) No. “Tumor” cells “Normal”cells 1 37.1 ± 4.0 60.7 ± 19.6 2 33.2 ± 3.8 45.1 ± 3.7  3 29.2 ± 1.951.2 ± 14.7 4 35.3 ± 3.7 36.0 ± 8.0  5 N/A 56.8 ± 18.5 6 N/A 41.7 ± 7.2 7 N/A 51.4 ± 16.0

The AFM analysis revealed average tip-cell surface adhesion ordetachment forces of about 34.2±5.3 pN and about 51.1±15.2 pN for all“tumor” cells and “normal” mesothelial cells, respectively (“tumor”cells, n=40; “normal” cells, n=48) (see FIG. 7). A two sampleindependent t-test conducted on the two cell populations indicated thatthe population average values were significantly different from eachother at the 95 percent confidence level (P=1.75×10⁻⁹). The averagenumber of observed tip-cell surface rupture (adhesion) events for all“tumor” cells and “normal” mesothelial cells was about 4.1±3.1 eventsand about 10.3±11.7 events, respectively (P=0.00168). When probed undersimilar conditions, the “normal” mesothelial cells exhibited anincreased cell surface adhesion, namely about 33 percent more adhesive,and a larger spread in the associated distribution as compared to“tumor” cells in the same clinical sample. Moreover, force curves takenon a bare substrate (before and after those performed on cells) revealedlittle to no variation between approach and subsequent retractioncurves, which would have been indicative of null adhesion.

Analysis of a clinical sample initially determined to include bothmalignant cells and benign mesothelial cells through cytomorphologicalexamination yielded average tip-cell surface adhesion values of about35.3±3.7 pN and about 36.0±8.0 pN for the morphologically classified“tumor” and “normal” populations, respectively (see Table 2, Sample No.4). However, these results indicated the presence of a single populationof malignant cells. Additional testing, including immunohistochemicalstaining for benign mesothelial cells (Calretinin) and malignant cells(B72.3 and Ber-Ep4), confirmed that the clinical sample includedpredominantly one malignant cell population, despite apparentmorphological differences between cells in the same population. Thus,cell surface adhesion analysis provides an additional biomarker forcancer cell evaluation and serves as a diagnostic aid in assaying humanpleural effusions and other cytological samples.

Example 6 Elasticity of Cells from Primary Breast Tumor Samples

Using a methodology similar to that of Example 1, elasticity ofpathologically defined human cancer cells and benign cells in primarytumor clinical samples was determined using an AFM. The samples werecollected from three different patients with suspected breast cancer.Table 3 below sets forth results of the AFM analysis. The resultsindicate a similar trend as observed for pleural effusion clinicalsamples, namely that cancer cells (here, primary tumor cancer cells) areless stiff than benign cells.

TABLE 3 Sample No. Classification Elasticity (kPa) 1 Tumor 0.70 ± 0.19 2Tumor 0.68 ± 0.28 3 Normal 1.84 ± 0.54

Example 7 Effect of Therapeutic Agents on Cell Elasticity

Using a methodology similar to that of Example 1, AFM measurements wereperformed to determine the effect of GTE on elasticity of cells obtainedfrom body cavity fluid samples. The samples included 4 samples collectedfrom patients with ovarian cancer, 3 samples collected from patientswith lung cancer, 2 samples collected from patients with breast cancer,and 1 sample collected from a healthy individual. Probable benign cells(“normal”) and probable malignant cells (“tumor”) were selected from thesamples for AFM analysis. The results of the AFM analysis for “tumor”cells and “normal” cells with and without exposure to GTE areillustrated in FIG. 8. The results indicate that exposure of malignantcells to GTE yields an increase in cell elasticity, and indicate thatAFM measurements can provide a biomarker for therapeutic agentevaluation.

A practitioner of ordinary skill in the art requires no additionalexplanation in developing the embodiments described herein but maynevertheless find some helpful guidance regarding the determination ofelasticity values using an AFM by examining the following references:Touhami, A. et al., Nanoscale Mapping of the Elasticity of MicrobialCells by Atomic Force Microscopy, Langmuir 19, 4539-4543 (2003); Rotsch,C. et al., Drug-induced Changes of Cytoskeletal Structure and Mechanicsin Fibroblasts: An Atomic Force Microscopy Study, Biophys. J. 78,520-535 (2000); Almqvist, N. et al., Elasticity and Adhesion ForceMapping Reveals Real-time Clustering of Growth Factor Receptors andAssociated Changes in Local Cellular Rheological Properties, Biophys J.,86(3), 1753-62 (2004); Rotsch, C. et al., AFM Imaging and ElasticityMeasurements on Living Rat Liver Macrophages, Cell BiologyInternational, 21(11), 685-96 (1997); and Matzke, R. et al., Direct,High-resolution Measurement of Furrow Stiffening During Division ofAdherent Cells, Nature Cell Biol. 3, 607-610 (2001); the disclosures ofwhich are incorporated herein by reference in their entireties. Apractitioner of ordinary skill in the art may also find some helpfulguidance regarding the determination of adhesiveness values using an AFMby examining the following references: van der Aa, B. et al., StretchingCell Surface Macromolecules by Atomic Force Microscopy, Langmuir,17(11), 3116-19 (2001); Cross, S. et al., Nanomechanical Properties ofGlucans and Associated Cell Surface Adhesion of Streptococcus MutansProbed by Atomic Force Microscopy Under In Situ Conditions,Microbiology, 153(9), 3124-32 (2007); Pelling, A. et al., NanoscaleVisualization and Characterization of Myxococcus Xanthus Cells withAtomic Force Microscopy, Proc. Natl. Acad. Sci. USA, 102(18), 6484-89(2005); Rief, M. et al., Reversible Unfolding of Individual TitinImmunoglobulin Domains by AFM, Science, 276(5315), 1109-12 (1997); andSen, S. et al., Indentation and Adhesive Probing of a Cell Membrane withAFM: Model and Experiments, Biophy. J., 89(5), 3203-13 (2005); thedisclosures of which are incorporated herein by reference in theirentireties.

Certain embodiments of the invention relate to a computer storageproduct with a computer-readable storage medium including datastructures and computer code for performing a set ofcomputer-implemented operations. The medium and computer code can bethose specially designed and constructed for the purposes of embodimentsof the invention, or they can be of the kind well known and available tothose having ordinary skill in the computer software arts. Examples ofcomputer-readable storage media include: magnetic media such as harddisks, floppy disks, and magnetic tape; optical media such as CompactDisc-Read Only Memories (“CD-ROMs”) and holographic devices;magneto-optical media such as floptical disks; and hardware devices thatare specially configured to store and execute computer code, such asApplication-Specific Integrated Circuits (“ASICs”), Programmable LogicDevices (“PLDs”), Read Only Memory (“ROM”) devices, and Random AccessMemory (“RAM”) devices. Examples of computer code include machine code,such as produced by a compiler, and files including higher-level codethat are executed by a computer using an interpreter. For example, anembodiment of the invention can be implemented using Java, C++, or otherobject-oriented programming language and development tools. Additionalexamples of computer code include encrypted code and compressed code.Another embodiment of the invention can be implemented in hardwiredcircuitry in place of, or in combination with, computer code.

While the invention has been described with reference to the specificembodiments thereof, it should be understood by those skilled in the artthat various changes may be made and equivalents may be substitutedwithout departing from the true spirit and scope of the invention asdefined by the appended claims. In addition, many modifications may bemade to adapt a particular situation, material, composition of matter,method, or process to the objective, spirit and scope of the invention.All such modifications are intended to be within the scope of the claimsappended hereto. In particular, while the methods disclosed herein havebeen described with reference to particular operations performed in aparticular order, it will be understood that these operations may becombined, sub-divided, or re-ordered to form an equivalent methodwithout departing from the teachings of the invention. Accordingly,unless specifically indicated herein, the order and grouping of theoperations are not limitations of the invention.

What is claimed is:
 1. A nanomechanical analysis system, comprising: anexpansion element; a cantilever having a first end and a second end, thefirst end of the cantilever being connected to the expansion element; aprobe disposed adjacent to the second end of the cantilever, the probebeing elongated and extending from the cantilever towards an uppersurface of a cell to be analyzed; a detector element disposed adjacentto the second end of the cantilever; an optical microscope disposedadjacent to a lower surface of the cell; a data processor connected tothe detector element; and a memory connected to the data processor,wherein the optical microscope is configured to provide visualexamination of the cell to position the probe with respect to a centralregion of the cell, wherein the expansion element is configured to movethe first end of the cantilever, such that the probe applies a stimulusto the cell, wherein the detector element is configured to produce anoutput indicative of an extent of deflection of the second end of thecantilever in accordance with a response of the cell to the stimulus,wherein the memory stores executable instructions to direct the dataprocessor to: based on the output of the detector element, determine aset of test values for the cell, the set of test values being indicativeof at least one of the cellular Young's modulus or adhesiveness of thecell with respect to the probe.
 2. The system of claim 1, wherein theprobe includes a tip that is configured to apply the stimulus to thecell, and the tip has a radius in the range of 5 nm to 900 nm.
 3. Thesystem of claim 1, wherein the executable instructions includeexecutable instructions to direct the data processor to: compare the setof test values with a set of reference values to determine a degree ofcorrespondence between the set of test values and the set of referencevalues, the set of reference values being associated with at least oneof a population of cancerous cells or a population of non-cancerouscells; and based on the degree of correspondence, produce an indicationof a biological state of the cell.
 4. The system of claim 3, wherein theexecutable instructions include executable instructions to direct thedata processor to: compare the set of test values with a pre-determinedrange of reference values associated with at least one of the populationof cancerous cells or the population of non-cancerous cells.
 5. Thesystem of claim 3, wherein the executable instructions includeexecutable instructions to direct the data processor to: determine a setof test characteristics associated with a distribution of the set oftest values; and compare the set of test characteristics with a set ofreference characteristics associated with a distribution of the set ofreference values.
 6. The system of claim 5, wherein the set of testcharacteristics is indicative of at least one of a Gaussian distributionor and a log-normal distribution.
 7. The system of claim 5, wherein theset of test characteristics is indicative of at least one of a mean or aspread of the distribution of the set of test values.
 8. The system ofclaim 3, wherein the cell is collected from a patient, and theexecutable instructions include executable instructions to direct thedata processor to: produce an indication of a likelihood of cancer inthe patient.
 9. The system of claim 3, wherein the cell is collectedfrom a patient, the population of cancerous cells corresponds to apopulation of metastatic cancer cells, and the executable instructionsinclude executable instructions to direct the data processor to: producean indication of a likelihood of metastatic cancer in the patient. 10.The system of claim 3, wherein the cell is collected from a patient, thepopulation of cancerous cells includes a first population of cancerouscells of a first degree of advancement and a second population ofcancerous cells of a second degree of advancement, the set of referencevalues includes a first set of reference values associated with thefirst population of cancerous cells and a second set of reference valuesassociated with the second population of cancerous cells, and theexecutable instructions include executable instructions to direct thedata processor to: compare the set of test values with the first set ofreference values to determine a degree of correspondence between the setof test values and the first set of reference values; and compare theset of test values with the second set of reference values to determinea degree of correspondence between the set of test values and the secondset of reference values.
 11. The system of claim 10, wherein theexecutable instructions include executable instructions to direct thedata processor to: produce an indication of a likelihood of cancer inthe patient of one of the first degree of advancement and the seconddegree of advancement.
 12. The system of claim 11, wherein theexecutable instructions include executable instructions to direct thedata processor to: select a therapeutic agent for the patient based onthe likelihood of cancer of one of the first degree of advancement andthe second degree of advancement.
 13. A nanomechanical analysis system,comprising: an expansion element; a cantilever having a first end and asecond end, the first end of the cantilever being connected to theexpansion element; a probe disposed adjacent to the second end of thecantilever, the probe being elongated and extending from the cantilever;a detector element disposed adjacent to the second end of thecantilever; a data processor connected to the detector element; and amemory connected to the data processor, wherein the expansion element isconfigured to move the first end of the cantilever, such that the probeapplies a first stimulus to a first cell and applies a second stimulusto a second cell, wherein the detector element is configured to producea first output indicative of a response of the first cell to the firststimulus, and is configured to produce a second output indicative of aresponse of the second cell to the second stimulus, and wherein thememory stores executable instructions to direct the data processor to:based on the first output, determine a first set of test values for thefirst cell, the first set of test values being indicative ofadhesiveness of the first cell with respect to the probe; based on thesecond output, determine a second set of test values for the secondcell, the second set of test values being indicative of adhesiveness ofthe second cell with respect to the probe; and based on the first set oftest values and the second set of test values, differentiate between thefirst cell and the second cell.
 14. The system of claim 13, wherein theprobe includes a tip having a radius in the range of 5 nm to 900 nm. 15.The system of claim 13, wherein the executable instructions includeexecutable instructions to direct the data processor to: select one ofthe first cell and the second cell.
 16. The system of claim 13, whereinthe executable instructions include executable instructions to directthe data processor to: compare the first set of test values with a setof reference values to determine a degree of correspondence between thefirst set of test values and the set of reference values; and comparethe second set of test values with the set of reference values todetermine a degree of correspondence between the second set of testvalues and the set of reference values.
 17. The system of claim 16,wherein the set of reference values is associated with at least one of apopulation of cancerous cells or a population of non-cancerous cells.18. The system of claim 13, wherein the executable instructions includeexecutable instructions to direct the data processor to: compare thefirst set of test values with the second set of test values.